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Background: Mood disorders (MDS) are a type of mental health illness that effects millions of people in the United States. Early prediction of MDS can give providers greater opportunity to treat these disorders. We hypothesized that longitudinal cardiovascular health (CVH) measurements would be informative for MDS prediction.Methods: To test this hypothesis, the American Heart Association's Guideline Advantage (TGA) dataset was used, which contained longitudinal EHR from 70 outpatient clinics. The statistical analysis and machine learning models were employed to identify the associations of the MDS and the longitudinal CVH metrics and other confounding factors.Results: Patients diagnosed with MDS consistently had a higher proportion of poor CVH compared to patients without MDS, with the largest difference between groups for Body mass index (BMI) and Smoking. Race and gender were associated with status of CVH metrics. Approximate 46% female patients with MDS had a poor hemoglobin A1C compared to 44% of those without MDS; 62% of those with MDS had poor BMI compared to 47% of those without MDS; 59% of those with MDS had poor blood pressure (BP) compared to 43% of those without MDS; and 43% of those with MDS were current smokers compared to 17% of those without MDS.Conclusions: Women and ethnoracial minorities with poor cardiovascular health measures were associated with a higher risk of development of MDS, which indicated the high utility for using routine medical records data collected in care to improve detection and treatment for MDS among patients with poor CVH. [ABSTRACT FROM AUTHOR]

Background: Patients with a substance use disorder (SUD) often present with co-occurring chronic conditions in primary care. Despite the high co-occurrence of chronic medical conditions and SUD, little is known about whether chronic condition outcomes or related service utilization in primary care varies between patients with versus without documented SUDs. This study examined whether having a SUD influenced the use of primary care services and common chronic condition outcomes for patients with diabetes, hypertension, and obesity.Methods: A longitudinal cohort observational study examined electronic health record data from 21 primary care clinics in Washington and Idaho to examine differences in service utilization and clinical outcomes for diabetes, hypertension, and obesity in patients with and without a documented SUD diagnosis. Differences between patients with and without documented SUD diagnoses were compared over a three-year window for clinical outcome measures, including hemoglobin A1c, systolic and diastolic blood pressure, and body mass index, as well as service outcome measures, including number of encounters with primary care and co-located behavioral health providers, and orders for prescription opioids. Adult patients (N = 10,175) diagnosed with diabetes, hypertension, or obesity before the end of 2014, and who had ≥2 visits across a three-year window including at least one visit in 2014 (baseline) and at least one visit occurring 12 months or longer after the 2014 visit (follow-up) were examined.Results: Patients with SUD diagnoses and co-occurring chronic conditions were seen by providers more frequently than patients without SUD diagnoses (p's < 0.05), and patients with SUD diagnoses were more likely to be prescribed opioid medications. Chronic condition outcomes were no different for patients with versus without SUD diagnoses.Discussion: Despite the higher visit rates to providers in primary care, a majority of patients with SUD diagnoses and chronic medical conditions in primary care did not get seen by co-located behavioral health providers, who can potentially provide and support evidence informed care for both SUD and chronic conditions. Patients with chronic medical conditions also were more likely to get prescribed opioids if they had an SUD diagnosis. Care pathway innovations for SUDs that include greater utilization of evidence-informed co-treatment of SUDs and chronic conditions within primary care settings may be necessary for improving care overall for patients with comorbid SUDs and chronic conditions. [ABSTRACT FROM AUTHOR]

Patients with a substance use disorder (SUD) often present with co-occurring chronic conditions in primary care. Despite the high co-occurrence of chronic medical conditions and SUD, little is known about whether chronic condition outcomes or related service utilization in primary care varies between patients with versus without documented SUDs. This study examined whether having a SUD influenced the use of primary care services and common chronic condition outcomes for patients with diabetes, hypertension, and obesity. A longitudinal cohort observational study examined electronic health record data from 21 primary care clinics in Washington and Idaho to examine differences in service utilization and clinical outcomes for diabetes, hypertension, and obesity in patients with and without a documented SUD diagnosis. Differences between patients with and without documented SUD diagnoses were compared over a three-year window for clinical outcome measures, including hemoglobin A1c, systolic and diastolic blood pressure, and body mass index, as well as service outcome measures, including number of encounters with primary care and co-located behavioral health providers, and orders for prescription opioids. Adult patients (N = 10,175) diagnosed with diabetes, hypertension, or obesity before the end of 2014, and who had ≥2 visits across a three-year window including at least one visit in 2014 (baseline) and at least one visit occurring 12 months or longer after the 2014 visit (follow-up) were examined. Patients with SUD diagnoses and co-occurring chronic conditions were seen by providers more frequently than patients without SUD diagnoses (p ' s < 0.05), and patients with SUD diagnoses were more likely to be prescribed opioid medications. Chronic condition outcomes were no different for patients with versus without SUD diagnoses. Despite the higher visit rates to providers in primary care, a majority of patients with SUD diagnoses and chronic medical conditions in primary care did not get seen by co-located behavioral health providers, who can potentially provide and support evidence informed care for both SUD and chronic conditions. Patients with chronic medical conditions also were more likely to get prescribed opioids if they had an SUD diagnosis. Care pathway innovations for SUDs that include greater utilization of evidence-informed co-treatment of SUDs and chronic conditions within primary care settings may be necessary for improving care overall for patients with comorbid SUDs and chronic conditions. • Patients with substance use disorder were seen more by providers in primary care. • Patients with substance use disorder received more opioid prescriptions. • Chronic condition outcomes did not differ. [ABSTRACT FROM AUTHOR]

We use prescription of statin medications and prescription of warfarin to explore the capacity of electronic health record data to (1) describe cohorts of patients prescribed these medications and (2) identify cohorts of patients with evidence of adverse events related to prescription of these medications. This study was conducted in the WWAMI region Practice and Research Network (WPRN)., a network of primary care practices across Washington, Wyoming, Alaska, Montana and Idaho DataQUEST, an electronic data-sharing infrastructure. We used electronic health record data to describe cohorts of patients prescribed statin or warfarin medications and reported the proportions of patients with adverse events. Among the 35,445 active patients, 1745 received at least one statin prescription and 301 received at least one warfarin prescription. Only 3 percent of statin patients had evidence of myopathy; 51 patients (17% of those prescribed warfarin) had a bleeding complication. Primary-care electronic health record data can effectively be used to identify patients prescribed specific medications and patients potentially experiencing medication adverse events. [ABSTRACT FROM AUTHOR]

Context: Digital therapeutics may be uniquely positioned to address challenges reported by providers in chronic pain (CP) management. Previous studies have shown patient-provider discordance in priorities for CP management, which can be addressed in digital therapeutics development to encourage implementation and use. Objective: To assess primary care providers' and patients' perceptions of CP treatment goals and motivators for use of a digital therapeutic delivering CP related behavioral interventions. Study Design: Quantitative surveys. Setting: Participants were recruited from four primary care clinics in Washington and Colorado, two patient support groups, and one research community stakeholder group. Population studied: The sample included 31 patients and 39 providers. Most patients identified as male (61.3%), non-Hispanic White (96.8%) and had experienced pain for one year or longer (90.3%). A mix of provider roles were included: primary care providers (46.2%), behavioral health providers (41.0%), clinical pharmacists (5.1%), and nurses (5.1%). All providers had experience treating patients with CP. Outcomes: Participants rated 10 CP treatment goals (e.g., quality of life, selfmanagement skills) and 11 motivators for use (e.g., coaching, insurance payment coverage) of digital therapeutics on a 5-point Likert-scale. Descriptive statistics and Chi-Square tests were computed. Results: Patients and providers differed in their perceptions of importance across all treatment goals. Patients' ratings of treatment goals ranged from least to very important, whereas providers uniformly rated all treatment goals as very or extremely important (p < .05), and provider ratings of importance were consistently higher than patients (p < .05). Patients and providers on average did not rate motivators for use very high and they differed in their perceptions across six specific motivators. Providers rated friend recommendations and coaching features as more likely to motivate use than patients did (p < .05). Providers tended to rate more uniformly than patients on motivators related to insurance covering most of the cost, it being recommended by a provider or friend, and if the program was personalized with coaching (p < .05). Conclusions: Incorporating digital therapeutics in routine primary care may help improve CP management by providing customizable features that address diverse treatment goals, and bridge differing perspectives between providers and patients. [ABSTRACT FROM AUTHOR]

Data variability is a commonly observed phenomenon in Electronic Health Records (EHR) data networks. A common question asked in scientific investigations of EHR data is whether the cross-site and -time variability reflects an underlying data quality error at one or more contributing sites versus actual differences driven by various idiosyncrasies in the healthcare settings. Although research analysts and data scientists have commonly used various statistical methods to detect and account for variability in analytic datasets, self service tools to facilitate exploring cross-organizational variability in EHR data warehouses are lacking and could benefit from meaningful data visualizations. DQe-v, an interactive, database-agnostic tool for visually exploring variability in EHR data provides such a solution. DQe-v is built on an open source platform, R statistical software, with annotated scripts and a readme document that makes it fully reproducible. To illustrate and describe functionality of DQe-v, we describe the DQe-v's readme document which includes a complete guide to installation, running the program, and interpretation of the outputs. We also provide annotated R scripts and an example dataset as supplemental materials. DQe-v offers a self service tool to visually explore data variability within EHR datasets irrespective of the data model. GitHub and CIELO offer hosting and distribution of the tool and can facilitate collaboration across any interested community of users as we target improving usability, efficiency, and interoperability. [ABSTRACT FROM AUTHOR]

Objective: Building federated data sharing architectures requires supporting a range of data owners, effective and validated semantic alignment between data resources, and consistent focus on end-users. Establishing these resources requires development methodologies that support internal validation of data extraction and translation processes, sustaining meaningful partnerships, and delivering clear and measurable system utility. We describe findings from two federated data sharing case examples that detail critical factors, shared outcomes, and production environment results.Methods: Two federated data sharing pilot architectures developed to support network-based research associated with the University of Washington's Institute of Translational Health Sciences provided the basis for the findings. A spiral model for implementation and evaluation was used to structure iterations of development and support knowledge share between the two network development teams, which cross collaborated to support and manage common stages.Results: We found that using a spiral model of software development and multiple cycles of iteration was effective in achieving early network design goals. Both networks required time and resource intensive efforts to establish a trusted environment to create the data sharing architectures. Both networks were challenged by the need for adaptive use cases to define and test utility.Conclusion: An iterative cyclical model of development provided a process for developing trust with data partners and refining the design, and supported measureable success in the development of new federated data sharing architectures. [ABSTRACT FROM AUTHOR]

Context: The widespread adoption of electronic health records (EHRs) offers significant opportunities to conduct research with clinical data from patients outside traditional academic research settings. Because EHRs are designed primarily for clinical care and billing, significant challenges are inherent in the use of EHR data for clinical and translational research. Efficient processes are needed for translational researchers to overcome these challenges. The Data QUEST Coordinating Center (DQCC), which oversees Data QUEST - a primary care EHR data sharing infrastructure - created processes that that guide EHR data extraction for clinical and translational research across these diverse practices. We describe these processes and their application in a case example. Case Description: The DQCC process for developing EHR data extractions not only supports researchers access to EHR data, but supports this access for the purpose of answering scientific questions. This process requires complex coordination across multiple domains, including: 1) understanding the context of EHR data; 2) creating and maintaining a governance structure to support exchange of EHR data; and 3) defining data parameters that are used in order to extract data from the EHR.1,2,3,4We use the Northwest-Alaska Pharmacogenomics Research Network (NWA-PGRN) as a case example that focuses on pharmacogenomic discovery and clinical applications to describe the DQCC process. The NWA-PGRN collaborates with Data QUEST to explore ways to leverage primary care EHR data to support pharmacogenomics research. Findings: Preliminary analysis on the case example shows that initial decisions about how researchers define the study population can influence study outcomes. Major Themes and Conclusions: The experience of the DQCC demonstrates that Coordinating Centers provide expertise in helping researchers understand the context of EHR data, create and maintain governance structures, and guide the definition of parameters for data extractions. This expertise is critical to support research with EHR data. Replication of these strategies through Coordinating Centers may lead to more efficient translational research. Investigators must also consider the impact of initial decisions in defining study groups that may potentially affect outcomes. Acknowledgements We acknowledge the Northwest Alaska Pharmacogenomics Research Network group for supporting the infrastructure and data collection, and Imara West for her assistance in data cleaning and analysis. This project was funded by the National Institute of General Medical Science (U01 GM092676) and the National Center for Advancing Translational Sciences of the National Institutes of Health (UL1TR000423). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health [ABSTRACT FROM AUTHOR]

Integrating behavioral health into primary care can improve access to behavioral health and patient health outcomes. We used 2017-2021 American Board of Family Medicine continuing certificate examination registration questionnaire responses to determine the characteristics of family physicians who work collaboratively with behavioral health professionals. With a 100% response rate, 38.8% of 25,222 family physicians reported working collaboratively with behavioral health professionals, with those working in independently owned practices and in the South having substantially lower rates. Future research exploring these differences could help develop strategies to support family physicians implement integrated behavioral health to improve care for patients in these communities. [ABSTRACT FROM AUTHOR]

Asian Americans have been understudied with respect to sexuality and rape and its contributory factors. Some attitudinal research has shown that Asian American college males tend to hold more rape-supportive beliefs than their White counterparts. Generally, this research treats ethnicity as a proxy for culture rather than examining specific facets of culture per se. The current study incorporated measures of misogynistic beliefs, acculturation, and ethnic identity to investigate these ethnic differences in rape-supportive attitudes. White ( n = 222) and Asian American ( n = 155) college men read an acquaintance rape vignette and evaluated it on four judgments: how much they blamed the perpetrator and the victim, how credible they viewed the victim's refusal, and to what degree they defined the event as rape. Consistent with previous research, Asian American men made more rape-supportive judgments than Whites. This relationship was partially mediated by misogynistic beliefs for all judgments except the extent to which they defined the vignette as rape. Among Asian Americans, acculturation was negatively associated with all four rape vignette judgments above and beyond generational status, and ethnic identity was positively associated with two of the four judgments above and beyond acculturation and generational status. These findings suggest that cultural constructs are relevant to understanding rape-supportive attitudes among Asian American men, and may be useful for promoting culturally enhanced theoretical models of rape and sexual assault prevention efforts, as well as a deeper understanding of cultural influences on sexuality. [ABSTRACT FROM AUTHOR]

Ethnoracial minority status contributes to an increased risk for posttraumatic stress disorder (PTSD) after trauma exposure, beyond other risk factors. A population-based sampling frame was used to examine the associations between ethnoracial groups and early PTSD symptoms while adjusting for relevant clinical and demographic characteristics. Acutely injured trauma center inpatients (N = 623) were screened with the PTSD Checklist. American Indian and African American patients reported the highest levels of posttraumatic stress and preinjury cumulative trauma burden. African American heritage was independently associated with an increased risk of higher acute PTSD symptom levels. Disparities in trauma history, PTSD symptoms, and event related factors emphasize the need for acute care services to incorporate culturally competent approaches for treating these diverse populations. [ABSTRACT FROM AUTHOR]

This study evaluates the effectiveness of a theoretically based rape prevention intervention with college men who were at high or low risk to perpetrate sexually coercive behavior. Participants (N = 146) are randomly assigned to the intervention or control group. Outcomes include rape myth acceptance, victim empathy, attraction to sexual aggression, sex-related alcohol expectancies, and behavioral indicators, measured across three time points. Positive effects are found for rape myth acceptance, victim empathy, attraction to sexual aggression, and behavioral intentions to rape. Only rape myth acceptance and victim empathy effects sustain at the 5-week follow-up. High-risk men are generally unaffected by the intervention although low-risk men produced larger effects than the entire sample. Results suggest rape prevention studies must assess risk status moderation effects to maximize prevention for high-risk men. More research is needed to develop effective rape prevention with men who are at high risk to rape. [ABSTRACT FROM AUTHOR]

While the early effects of the COVID-19 pandemic on the United States labor market are well-established, less is known about the long-term impact of SARS-CoV-2 infection and Long COVID on employment. To address this gap, we analyzed self-reported data from a prospective, national cohort study to estimate the effects of SARS-CoV-2 symptoms at three months post-infection on missed workdays and return to work. The analysis included 2,939 adults in the Innovative Support for Patients with SARS-CoV-2 Infections Registry (INSPIRE) study who tested positive for their initial SARS-CoV-2 infection at the time of enrollment, were employed before the pandemic, and completed a baseline and three-month electronic survey. At three months post-infection, 40.8% of participants reported at least one SARS-CoV-2 symptom and 9.6% of participants reported five or more SARS-CoV-2 symptoms. When asked about missed work due to their SARS-CoV-2 infection at three months, 7.2% of participants reported missing ≥10 workdays and 13.9% of participants reported not returning to work since their infection. At three months, participants with ≥5 symptoms had a higher adjusted odds ratio of missing ≥10 workdays (2.96, 95% CI 1.81–4.83) and not returning to work (2.44, 95% CI 1.58–3.76) compared to those with no symptoms. Prolonged SARS-CoV-2 symptoms were common, affecting 4-in-10 participants at three-months post-infection, and were associated with increased odds of work loss, most pronounced among adults with ≥5 symptoms at three months. Despite the end of the federal Public Health Emergency for COVID-19 and efforts to "return to normal", policymakers must consider the clinical and economic implications of the COVID-19 pandemic on people's employment status and work absenteeism, particularly as data characterizing the numerous health and well-being impacts of Long COVID continue to emerge. Improved understanding of risk factors for lost work time may guide efforts to support people in returning to work. [ABSTRACT FROM AUTHOR]

Background: In response to the opioid crisis in the United States, population-level prescribing of opioids has been decreasing; there are concerns, however, that dose reductions are related to potential adverse events. Objective: Examine associations between opioid dose reductions and risk of 1-month potential adverse events (emergency department (ED) visits, opioid overdose, benzodiazepine prescription fill, all-cause mortality). Design: This observational cohort study used electronic health record and claims data from eight United States health systems in a prescription opioid registry (Clinical Trials Network-0084). All opioid fills (excluding buprenorphine) between 1/1/2012 and 12/31/2018 were used to identify baseline periods with mean morphine milligram equivalents daily dose of ≥ 50 during six consecutive months. Patients: We identified 60,040 non-cancer patients with ≥ one 2-month dose reduction period (600,234 unique dose reduction periods). Main Measures: Analyses examined associations between dose reduction levels (1– < 15%, 15– < 30%, 30– < 100%, 100% over 2 months) and potential adverse events in the month following a dose reduction using logistic regression analysis, adjusting for patient characteristics. Key Results: Overall, dose reduction periods involved mean reductions of 18.7%. Compared to reductions of 1– < 15%, dose reductions of 30– < 100% were associated with higher odds of ED visits (OR 1.14, 95% CI 1.10, 1.17), opioid overdose (OR 1.41, 95% CI 1.09–1.81), and all-cause mortality (OR 1.39, 95% CI 1.16–1.67), but lower odds of a benzodiazepine fill (OR 0.83, 95% CI 0.81–0.85). Dose reductions of 15– < 30%, compared to 1– < 15%, were associated with higher odds of ED visits (OR 1.08, 95% CI 1.05–1.11) and lower odds of a benzodiazepine fill (OR 0.93, 95% CI 0.92–0.95), but were not associated with opioid overdose and all-cause mortality. Conclusions: Larger reductions for patients on opioid therapy may raise risk of potential adverse events in the month after reduction and should be carefully monitored. [ABSTRACT FROM AUTHOR]

Insurance companies and the Centers for Medicaid and Medicare Services are shifting from reimbursing health providers a fixed amount for a service to reimbursement based in part on patients' outcomes. This approach is called value-based care (VBC) and includes a wide range of programs. Although the behavioral health providers that have been impacted by VBC to date are primarily those in larger health systems, use of VBC is expanding as payors seek to combat rising health care costs and increase transparency and accountability for health services. Thus, behavioral health providers need to know about VBC models and their impact as well as steps they can take to be better prepared for this shift. Public Significance Statement: Insurance companies and Medicare/Medicaid are increasingly basing their payment for health care on patients' outcomes. This value-based care approach is new for most behavioral health care providers and therefore requires learning these new systems and preparing for change. [ABSTRACT FROM AUTHOR]

The United States is facing a social isolation and loneliness crisis. In response, the US Surgeon General issued an advisory in May 2023 recommending actions that health care, community programs, and social services can take to collaboratively improve social connection. Primary care has a critical role to play in implementing the Surgeon General's recommendations. We present social isolation and loneliness as medical issues and highlight next steps for the primary care sector to combat this epidemic. [ABSTRACT FROM AUTHOR]

Context: Rising prevalence of both mental health and substance use disorders, exacerbated by the COVID-19 pandemic, have left many individuals with limited access to behavioral health care. Integrating behavioral health into primary care has been shown to increase behavioral healthcare access and improve outcomes. However, little is known about the characteristics and distribution of family physicians working collaboratively with behavioral health clinicians. Objective: To describe the demographic and practice characteristics of family physicians who work collaboratively with behavioral health clinicians. Study design and Analysis: Cross-sectional survey with chi-squared independence tests and logistic regression. Setting or Dataset: The American Board of Family Medicine (ABFM) 2017-2021 continuing certification examination registration questionnaire, which is completed by every diplomate during registration for recertification. Population studied: ABFM-certified family physicians. Outcome measures: The primary outcome was self-report of working collaboratively in their primary practice setting with behavioral health clinicians. We examined associations with demographic, practice and geographic characteristics. Results: This survey mechanism achieves a 100% response rate. Among 25,222 responding family physicians in continuity care settings, 38.8% reported working collaboratively with any behavioral health clinician. This trend increased from 34.8% in 2017 to 43.0% in 2021. Those working in an independentlyowned practice had lower odds of working collaboratively with behavioral health clinicians (OR = 0.341) while those working as faculty had higher odds (OR = 2.319). Substantial geographic state-level variation in Vermont with low levels of collaboration in the South. Conclusions: Rates of integration appear to be rising nationally, though significant variation exists, with far less integration reported from family physicians in independent and Southern practices. Inequitable access to mental health services suggests the need for further research to explore reasons for these disparities exist and how best to support further integration, to better support patient health and to improve health outcomes. [ABSTRACT FROM AUTHOR]

Background Long-term symptoms following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are a major concern, yet their prevalence is poorly understood. Methods We conducted a prospective cohort study comparing adults with SARS-CoV-2 infection (coronavirus disease-positive [COVID+]) with adults who tested negative (COVID−), enrolled within 28 days of a Food and Drug Administration (FDA)-approved SARS-CoV-2 test result for active symptoms. Sociodemographic characteristics, symptoms of SARS-CoV-2 infection (assessed with the Centers for Disease Control and Prevention [CDC] Person Under Investigation Symptom List), and symptoms of post-infectious syndromes (ie, fatigue, sleep quality, muscle/joint pains, unrefreshing sleep, and dizziness/fainting, assessed with CDC Short Symptom Screener for myalgic encephalomyelitis/chronic fatigue syndrome) were assessed at baseline and 3 months via electronic surveys sent via text or email. Results Among the first 1000 participants, 722 were COVID+ and 278 were COVID−. Mean age was 41.5 (SD 15.2); 66.3% were female, 13.4% were Black, and 15.3% were Hispanic. At baseline, SARS-CoV-2 symptoms were more common in the COVID+ group than the COVID− group. At 3 months, SARS-CoV-2 symptoms declined in both groups, although were more prevalent in the COVID+ group: upper respiratory symptoms/head/eyes/ears/nose/throat (HEENT; 37.3% vs 20.9%), constitutional (28.8% vs 19.4%), musculoskeletal (19.5% vs 14.7%), pulmonary (17.6% vs 12.2%), cardiovascular (10.0% vs 7.2%), and gastrointestinal (8.7% vs 8.3%); only 50.2% and 73.3% reported no symptoms at all. Symptoms of post-infectious syndromes were similarly prevalent among the COVID+ and COVID− groups at 3 months. Conclusions Approximately half of COVID+ participants, as compared with one-quarter of COVID− participants, had at least 1 SARS-CoV-2 symptom at 3 months, highlighting the need for future work to distinguish long COVID. Clinical Trials Registration NCT04610515. [ABSTRACT FROM AUTHOR]

Simple Summary: Lung cancer is the most common cause of cancer related death in the US, but survival is far better when people are diagnosed at an earlier stage. There are currently no clinical quality measures that are routinely used to measure the quality or timeliness of diagnosis of lung cancer in the US. We used Natural Language Processing (NLP) to extract information on the symptoms and signs that had been recorded in the electronic medical records of patients presenting in ambulatory care over the 2 years prior to their diagnosis with lung cancer. We found that the time from the first recorded symptoms/signs associated with lung cancer to diagnosis was 570 days. The time intervals from chest CT or chest X-ray imaging to diagnosis, and from specialist consultation to diagnosis were shorter—at 43 and 72 days, respectively. Advanced techniques such as NLP can be used to extract detailed information from electronic medical records, that could potentially be used to create clinical quality measures with the goal of improving the timeliness of diagnosis of this cancer. The diagnosis of lung cancer in ambulatory settings is often challenging due to non-specific clinical presentation, but there are currently no clinical quality measures (CQMs) in the United States used to identify areas for practice improvement in diagnosis. We describe the pre-diagnostic time intervals among a retrospective cohort of 711 patients identified with primary lung cancer from 2012–2019 from ambulatory care clinics in Seattle, Washington USA. Electronic health record data were extracted for two years prior to diagnosis, and Natural Language Processing (NLP) applied to identify symptoms/signs from free text clinical fields. Time points were defined for initial symptomatic presentation, chest imaging, specialist consultation, diagnostic confirmation, and treatment initiation. Median and interquartile ranges (IQR) were calculated for intervals spanning these time points. The mean age of the cohort was 67.3 years, 54.1% had Stage III or IV disease and the majority were diagnosed after clinical presentation (94.5%) rather than screening (5.5%). Median intervals from first recorded symptoms/signs to diagnosis was 570 days (IQR 273–691), from chest CT or chest X-ray imaging to diagnosis 43 days (IQR 11–240), specialist consultation to diagnosis 72 days (IQR 13–456), and from diagnosis to treatment initiation 7 days (IQR 0–36). Symptoms/signs associated with lung cancer can be identified over a year prior to diagnosis using NLP, highlighting the need for CQMs to improve timeliness of diagnosis. [ABSTRACT FROM AUTHOR]

Introduction: Integrating behavioral health in primary care improves quality of care and outcomes for patients with comorbid conditions. Shortage of a trained behavioral health workforce limits adoption. Professional psychology training programs contribute to recruitment, retention, and development of skilled providers, who value and deliver behavioral health services in primary care. This study interviewed a cohort of established psychology training programs in real-world, state-wide clinical primary care settings and identified their strategies and challenges with teaching practices and program resources that impact the robust quality of training. Method: Between December 2020 and March 2021, we conducted semistructured interviews with 12 licensed psychologists who oversaw nine integrated primary care psychology training programs at the internship and postdoctoral levels across Washington State. Data were analyzed using a thematic approach. Results: Programs taught psychology trainees about integrated primary care via extensive onboarding, modeling and shadowing, structured learning environment, interprofessional education opportunities, flexible and cross-disciplinary supervision, and a psychologically safe space. Teaching challenges included balancing scheduled and curbside supervision, pivoting to telehealth, and aligning trainee expectations and program requirements. Training programs were funded through different and multiple sources, but most lacked a stable funding mechanism, compounded by barriers for psychology trainees to bill for services, a lack of control over organization's budgeting decisions, and instability in funding renewal. Conclusion: Synergistic support from program, organization, and system/policy levels are needed to align teaching activities with clinical practice environments and invest in the growth and sustainability of psychology training programs on integrated primary care. [ABSTRACT FROM AUTHOR]

Background and Aim: There is no gold‐standard and considerable heterogeneity in outcome measures used to evaluate treatments for opioid use disorder (OUD) along the opioid treatment cascade. The aim of this study was to develop the US National Institute on Drug Abuse (NIDA) National Drug Abuse Treatment Clinical Trials Network (CTN) opioid use disorder core outcomes set (OUD–COS). Design: Four‐round, e‐Delphi expert panel consensus study and plenary research group discussion and targeted consultation. Setting: United States. Participants: A panel of 25 members including clinical practitioners, clinical researchers and administrative staff from the CTN, the network's affiliated clinical and community sites and the NIDA Centre for the CTN. Measurements From a pool of 24 candidate items in four domains (biomedical/disease status; behaviors, symptoms and functioning; opioid treatment cascade; and morbidity and mortality), the panel completed an on‐line questionnaire to rank items with defined specification on a 9‐point scale for importance, with a standard 70% consensus criterion. Findings After the fourth round of the questionnaire and subsequent discussion, consensus was reached for five outcomes: two patient‐reported (global impression of improvement and incident non‐fatal overdose); one clinician‐reported (illicit/non‐medical drug toxicology); and two from administrative records (duration of treatment and fatal opioid poisoning). Conclusions: An e‐Delphi consensus study has produced the US National Institute on Drug Abuse (NIDA) National Drug Abuse Treatment Clinical Trials Network opioid use disorder core outcomes set (version 1) for opioid use disorder treatment efficacy and effectiveness research. [ABSTRACT FROM AUTHOR]

Background: Reports on medium and long-term sequelae of SARS-CoV-2 infections largely lack quantification of incidence and relative risk. We describe the rationale and methods of the Innovative Support for Patients with SARS-CoV-2 Registry (INSPIRE) that combines patient-reported outcomes with data from digital health records to understand predictors and impacts of SARS-CoV-2 infection. Methods: INSPIRE is a prospective, multicenter, longitudinal study of individuals with symptoms of SARS-CoV-2 infection in eight regions across the US. Adults are eligible for enrollment if they are fluent in English or Spanish, reported symptoms suggestive of acute SARS-CoV-2 infection, and if they are within 42 days of having a SARS-CoV-2 viral test (i.e., nucleic acid amplification test or antigen test), regardless of test results. Recruitment occurs in-person, by phone or email, and through online advertisement. A secure online platform is used to facilitate the collation of consent-related materials, digital health records, and responses to self-administered surveys. Participants are followed for up to 18 months, with patient-reported outcomes collected every three months via survey and linked to concurrent digital health data; follow-up includes no in-person involvement. Our planned enrollment is 4,800 participants, including 2,400 SARS-CoV-2 positive and 2,400 SARS-CoV-2 negative participants (as a concurrent comparison group). These data will allow assessment of longitudinal outcomes from SARS-CoV-2 infection and comparison of the relative risk of outcomes in individuals with and without infection. Patient-reported outcomes include self-reported health function and status, as well as clinical outcomes including health system encounters and new diagnoses. Results: Participating sites obtained institutional review board approval. Enrollment and follow-up are ongoing. Conclusions: This study will characterize medium and long-term sequelae of SARS-CoV-2 infection among a diverse population, predictors of sequelae, and their relative risk compared to persons with similar symptomatology but without SARS-CoV-2 infection. These data may inform clinical interventions for individuals with sequelae of SARS-CoV-2 infection. [ABSTRACT FROM AUTHOR]

Primary care has increasingly adopted integrated behavioral health (IBH) practices to enhance overall care. The IBH Cross-Model Framework clarifies the core processes and structures of IBH, but little is known about how practices vary in the implementation of these processes and structures. This study aimed to describe clusters of clinics using the IBH Cross-Model Framework for a large sample of primary care clinics, as well as contextual variables associated with differences in implementation. Primary care clinics (N = 102) in Minnesota reported their level of implementation across 18 different components of IBH via the site self-assessment (SSA). The components were mapped to all five principles and four of the nine structures of the IBH Cross-Model Framework. latent class analysis was used to identify unique clusters of IBH components from the SSA across the IBH Cross-Model Framework's processes and structures. Latent classes were then regressed onto context variables. A four-class model was determined to be the best fit: Low IBH (39.6%), Structural IBH (7.9%), Partial IBH (29.4%), and Strong IBH (23.1%). Partial IBH clinics were more urban than the other three classes, lower in SES risk than Structural IBH clinics, and located in smaller organizations than Strong IBH clinics. There were no differences between classes in race/ethnicity of the clinic area or practice size. Four groups of IBH implementation were identified representing unique profiles of integration. These clusters may represent patterns of community-based implementation of IBH that indicate easier and more challenging aspects of IBH implementation. [ABSTRACT FROM AUTHOR]

Background: A lack of consensus on the optimal outcome measures to assess the efficacy and effectiveness of interventions for the treatment of opioid use disorder (OUD) has hampered the pooling of research data for evidence synthesis and clinical guidelines. A core outcome set (COS) is a minimum set of outcome measures that are recommended for all studies of a particular condition. The National Drug Abuse Treatment Clinical Trials Network (CTN) Core Outcome Set for OUD (COS-OUD) is a development study to identify core constructs, meaningful outcomes, and their optimal measurement for all efficacy and effectiveness studies of OUD treatment and service delivery.Methods/design: Overseen by an expert workgroup, a modified, stepwise, e-Delphi methodology will be used to gain consensus among a panel of clinical practitioners and researchers involved in the treatment of OUD, who are members of the CTN. Sequential rounds of anonymous, online questionnaires will be used to identify, rate the importance of, and refine a core outcome set. A consensus threshold will be achieved if at least 70% of the panel rate the measure as critical for inclusion in the COS-OUD. Where consensus is not reached or there are suggestions for new measures, these will be brought forward to a further round of review prior to a consensus meeting. Products from this study will be communicated via peer-reviewed scientific journals and conferences.Discussion: This initiative will develop a COS for OUD intervention trials, treatment studies, and service delivery and will support the pooling of research and clinical practice data and efforts to develop measurement-based care within the OUD treatment cascade.Trial Registration: http://www.comet-initiative.org/Studies/Details/1579. [ABSTRACT FROM AUTHOR]

Background: Most people with alcohol or opioid use disorders (AUD or OUD) are not diagnosed or treated for these conditions in primary care. This study takes a critical step toward quantifying service gaps and directing improvement efforts for AUD and OUD by using electronic health record (EHR) data from diverse primary care organizations to quantify the extent to which AUD and OUD are underdiagnosed and undertreated in primary care practices.Methods: We extracted and integrated diagnosis, medication, and behavioral health visit data from the EHRs of 21 primary care clinics within four independent healthcare organizations representing community health centers and rural hospital-associated clinics in the Pacific Northwest United States. Rates of documented AUD and OUD diagnoses, pharmacological treatments, and behavioral health visits were evaluated over a two-year period (2015-2016).Results: Out of 47,502 adult primary care patients, 1476 (3.1%) had documented AUD; of these, 115 (7.8%) had orders for AUD medications and 271 (18.4%) had at least one documented visit with a non-physician behavioral health specialist. Only 402 (0.8%) patients had documented OUD, and of these, 107 (26.6%) received OUD medications and 119 (29.6%) had at least one documented visit with a non-physician behavioral health specialist. Rates of AUD diagnosis and AUD and OUD medications were higher in clinics that had co-located non-physician behavioral health specialists.Conclusions: AUD and OUD are underdiagnosed and undertreated within a sample of independent primary care organizations serving mostly rural patients. Primary care organizations likely need service models, technologies, and workforces, including non-physician behavioral health specialists, to improve capacities to diagnose and treat AUD and OUD. [ABSTRACT FROM AUTHOR]

The Centers for Disease Control and Prevention's 2022 Clinical Practice Guideline for Prescribing Opioids for Pain cautioned that inflexible opioid prescription duration limits may harm patients. Information about the relationship between initial opioid prescription duration and a subsequent refill could inform prescribing policies and practices to optimize patient outcomes. We assessed the association between initial opioid duration and an opioid refill prescription. We conducted a retrospective cohort study of adults ≥19 years of age in 10 US health systems between 2013 and 2018 from outpatient care with a diagnosis for back pain without radiculopathy, back pain with radiculopathy, neck pain, joint pain, tendonitis/bursitis, mild musculoskeletal pain, severe musculoskeletal pain, urinary calculus, or headache. Generalized additive models were used to estimate the association between opioid days' supply and a refill prescription. Overall, 220,797 patients were prescribed opioid analgesics upon an outpatient visit for pain. Nearly a quarter (23.5%) of the cohort received an opioid refill prescription during follow-up. The likelihood of a refill generally increased with initial duration for most pain diagnoses. About 1 to 3 fewer patients would receive a refill within 3 months for every 100 patients initially prescribed 3 vs. 7 days of opioids for most pain diagnoses. The lowest likelihood of refill was for a 1-day supply for all pain diagnoses, except for severe musculoskeletal pain (9 days' supply) and headache (3–4 days' supply). Long-term prescription opioid use increased modestly with initial opioid prescription duration for most but not all pain diagnoses examined. • Most patients initially prescribed opioids for acute pain did not receive a refill. • Continued prescription opioid use generally increased with initial opioid duration. • Association of initial opioid days' supply and a refill varied by pain diagnosis. • Flexible prescription opioid duration limits should be considered. [ABSTRACT FROM AUTHOR]

Purpose: Six key elements of opioid medication management redesign in primary care have been previously identified. Here, we examine the effect of implementing these Six Building Blocks on opioid-prescribing practices.Methods: Six rural-serving organizations with 20 clinic locations received support for 15 months during the period October 2015 to May 2017 to implement the Six Building Blocks. Patients undergoing long-term opioid therapy (LtOT) at these study sites were compared with patients undergoing LtOT enrolled in a regional health plan who did not receive care at the study sites but who resided in the same primary care service areas (control group). Outcomes were monthly trend in the proportion of patients undergoing LtOT prescribed a ≥100 morphine equivalent dose (MED) of opioids daily and the total number of patients receiving an opioid prescription. An interrupted time series using difference-indifference analysis was used for tests of significance.Results: The proportion of patients prescribed a ≥100 MED of opioids daily decreased 2.2% (11.8% to 9.6%) among patients at the intervention clinics and 1.3% (14.0% to 12.7%) among patients in the control group. The rate of decrease was significantly greater among study patients than among patients in the control group (P = .018). The rate of decrease in the number of patients on LtOT at intervention clinics increased during the intervention period compared with the preintervention period (P <.001).Conclusions: Efforts to redesign opioid medication management in primary care resulted in a significant decrease in opioid prescribing. Future research is needed to determine if these results are generalizable to other settings and to assess implications for patient-reported outcomes. [ABSTRACT FROM AUTHOR]

Context: Digital therapeutics are growing as a solution to improve access and quality of care. Increasing evidence has shown the efficacy of digital therapeutics in managing pain for patients, but they are underutilized by primary care providers who see over half of the patients with chronic pain. Engaging providers to develop and use digital therapeutics with patients in chronic pain management has become necessary. Objective: This study explored primary care providers' challenges and strategies in chronic pain management to identify needs and practice gaps that inform development of digital therapeutics for chronic pain. Study Design: Qualitative study, using a human-centered design approach. Setting: Eleven providers from four primary care clinics in Washington and Colorado participated in semistructured interviews between July and October 2021. Population studied: The sample (N=11) included seven primary care physicians, two behavioral health providers, one physician assistant and one nurse. Most providers worked in clinics affiliated with urban, academic health systems or in federally qualified health centers. Outcomes: Interviews focused on provider goals in chronic pain management, challenges and strategies used, and perceptions of digital therapeutics. Results: Four themes related to provider needs emerged: patient-provider alliance, team-based care, tracking and monitoring, and social determinants of health. Providers desired resources to streamline pain education, counseling, and goal setting with patients. Greater accessibility to multidisciplinary care team consultations and nonpharmacological pain treatments would be beneficial to providers and patients. Infrastructure and systems are needed for providers to systematically track and monitor patients' pain. Providers requested assistance with connecting underserved patients to wraparound social services and addressing healthcare access barriers. Conclusion: Digital therapeutics for chronic pain would benefit from incorporating multimodal features that strengthen patient-provider alliance, increase access to non-pharmacological treatment options, support population health tracking and management, and provide equitable solutions that require lower sophistication of device and Internet access. Leveraging digital therapeutics in healthcare settings requires meeting provider needs at individual care and system levels. [ABSTRACT FROM AUTHOR]

Background Diagnostic imaging is often the first step in evaluating patients with back pain and likely functions as a “gateway” to a subsequent cascade of interventions. However, lumbar spine imaging frequently reveals incidental findings among normal, pain-free individuals suggesting that treatment of these “abnormalities” may not be warranted. Our prior work suggested that inserting the prevalence of imaging findings in patients without back pain into spine imaging reports may reduce subsequent interventions. We are now conducting a pragmatic cluster randomized clinical trial to test the hypothesis that inserting this prevalence data into lumbar spine imaging reports for studies ordered by primary care providers will reduce subsequent spine-related interventions. Methods/design We are using a stepped wedge design that sequentially randomizes 100 primary care clinics at four health systems to receive either standard lumbar spine imaging reports, or reports containing prevalence data for common imaging findings in patients without back pain. We capture all outcomes passively through the electronic medical record. Our primary outcome is spine-related intervention intensity based on Relative Value Units (RVUs) during the following year. Secondary outcomes include subsequent prescriptions for opioid analgesics and cross-sectional lumbar spine re-imaging. Discussion If our study shows that adding prevalence data to spine imaging reports decreases subsequent back-related RVUs, this intervention could be easily generalized and applied to other kinds of testing, as well as other conditions where incidental findings may be common. Our study also serves as a model for cluster randomized trials that are minimal risk and highly pragmatic. [ABSTRACT FROM AUTHOR]

Abstract: Objective: The objective of the study was to develop and implement a stepped collaborative care intervention targeting posttraumatic stress disorder (PTSD) and related comorbidities to enhance the population impact of early trauma-focused interventions. Method: We describe the design and implementation of the Trauma Survivors Outcomes and Support study. An interdisciplinary treatment development team was composed of trauma surgical, clinical psychiatric and mental health services “change agents” who spanned the boundaries between frontline trauma center clinical care and acute care policy. Mixed method clinical epidemiologic and clinical ethnographic studies informed the development of PTSD screening and intervention procedures. Results: Two hundred seven acutely injured trauma survivors with high early PTSD symptom levels were randomized into the study. The stepped collaborative care model integrated care management (i.e., posttraumatic concern elicitation and amelioration, motivational interviewing and behavioral activation) with cognitive behavioral therapy and pharmacotherapy targeting PTSD. The model was feasibly implemented by frontline acute care masters in social work and nurse practioner providers. Conclusions: Stepped care protocols targeting PTSD may enhance the population impact of early interventions developed for survivors of individual and mass trauma by extending the reach of collaborative care interventions to acute care medical settings and other nonspecialty posttraumatic contexts. [Copyright &y& Elsevier]

Explanatory models of sexual aggression were examined among mainland Asian American (n = 222), Hawaiian Asian American (n = 127), and European American men (n = 399). The Malamuth et al. (N. M. Malamuth, D. Linz, C. L. Heavey, G. Barnes, & M. Acker, 1995; N. M. Malamuth, R. i. Sockloskie, M. P. Koss, & I. S. Tanaka, 1991) confluence model of sexual aggression, which posits impersonal sex and hostile masculinity as paths to sexual aggression, was consistently supported. Culture-specific moderators of sexual aggression were also identified. Whereas loss of face was a protective factor against sexual aggression in the Asian American samples, it generally was not a protective factor among European Americans. These findings are not a function of actual or perceived minority status. An implication is that theoretical models may need to be augmented with cultural constructs for optimal application in certain ethnic group contexts. [ABSTRACT FROM AUTHOR]